Zhang Ruoyi, Ling Xin, Guo Xianwen, Ding Zhen
Department of Gastroenterology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, China.
Int J Mol Sci. 2025 Feb 22;26(5):1899. doi: 10.3390/ijms26051899.
Numerous animal experiments have implicated ferroptosis in the pathogenesis of acute pancreatitis (AP). Nonetheless, due to sampling constraints, the precise role of ferroptosis in the human body during AP remains elusive. Method: Peripheral blood sequencing data of patients with acute pancreatitis (GSE194331) were obtained from the Gene Expression Omnibus (GEO) database. We analyzed differentially expressed genes whose expression increased or decreased with increasing disease severity and intersected them with the ferroptosis gene set to identify ferroptosis-related driver genes for the disease. The hub genes were selected using machine learning algorithms, and a nomogram diagnosis model was constructed. Clinical samples, animal models, and an in vitro experiment were also used for validation. The investigation unveiled 22 ferroptosis-related driver genes, and we identified three hub genes, , , and , by employing two machine learning algorithms. and exhibit robust correlations with various immune cells. The disease diagnosis model constructed utilizing these three genes demonstrated high sensitivity and specificity (AUC = 0.889). In the in vitro experiments, we discovered for the first time that ferroptosis occurs in pancreatic duct cells during acute pancreatitis, and that MGST1 is significantly upregulated in duct cells, where it plays a crucial role in negatively regulating ferroptosis via the ACSL4/GPX4 axis. In addition, overexpression of MGST1 protects ductal cells from inflammatory damage. In our investigation, we explored the mechanisms of ferroptosis in immune cells and pancreatic duct cells in patients with AP. These results highlight a potential pathway for the early diagnosis and treatment of acute pancreatitis.
大量动物实验表明铁死亡与急性胰腺炎(AP)的发病机制有关。然而,由于采样限制,铁死亡在AP患者体内的确切作用仍不清楚。方法:从基因表达综合数据库(GEO)获取急性胰腺炎患者的外周血测序数据(GSE194331)。我们分析了随着疾病严重程度增加而表达升高或降低的差异表达基因,并将它们与铁死亡基因集进行交叉分析,以确定该疾病中铁死亡相关的驱动基因。使用机器学习算法选择枢纽基因,并构建列线图诊断模型。还使用临床样本、动物模型和体外实验进行验证。研究发现了22个铁死亡相关的驱动基因,通过两种机器学习算法,我们确定了三个枢纽基因,即 、 和 。 和 与各种免疫细胞表现出强烈的相关性。利用这三个基因构建的疾病诊断模型具有较高的敏感性和特异性(AUC = 0.889)。在体外实验中,我们首次发现急性胰腺炎期间胰腺导管细胞会发生铁死亡,并且MGST1在导管细胞中显著上调,它通过ACSL4/GPX4轴在负调控铁死亡中起关键作用。此外,MGST1的过表达可保护导管细胞免受炎症损伤。在我们的研究中,我们探索了AP患者免疫细胞和胰腺导管细胞中铁死亡的机制。这些结果突出了急性胰腺炎早期诊断和治疗的潜在途径。